Light Detection and Ranging (LiDAR)

LiDAR is a remote sensing technology that operates on a similar fashion to RADAR sensing, but uses laser light instead of radio waves. LiDAR scanners, which can be either ground-based or airborne/spaceborne, generate 3D models of their environment by emitting pulses of light and precisely timing their reflections from a target, or put differently, the sensor-target-sensor return trip distance. This timing information is used to create a point cloud, a set of possibly millions of 3D coordinates that represent laser-target interactions. A relatively novel development in the LiDAR arena, waveform LiDAR, extends this principle to full-waveform digitization, i.e., the signal is not discretized into separate point returns, but the entire backscattered signal is recorded (see images below).

LiDAR research is an emerging field within imaging science that has many potential applications in areas ranging from environmental studies to emergency response. LIAS has a strong LiDAR focus in both these arenas:

Seneca LiDAR: A discrete return LiDAR surface showing ground-only returns. Note the removed building footprints and flood plain topography - these data will be used for flood response managementSeneca LiDAR: A discrete return LiDAR surface showing all returns. Note the creek (west), building footprints, and vegetation - these data will be used for flood response management

LiDAR algorithm development is required to go from high data volume point clouds to useful structural products, such as topography and vegetation structure. This research will form one of the core activities of the IPLER initiative, given the usefulness of structural data in rural and urban environments. We are collaborating with an IPLER partner, Kucera International, to collect lidar data and develop operational algorithms. MS students will be sponsored as part of the research and education component of IPLER, which will allow these students to develop into informed researchers, technologists, or disaster responders upon graduation.

Deconvolving waveforms: Research around the pre-processing of waveform LiDAR data focuses on physical modeling of waveform interactionsStructural modeling: These deconvolved waveforms can then be used for extraction of structural parameters

Padding

Waveform visualization: LiDAR waveforms as visualized via intensity plotted in three dimensionsWaveform simulation: Waveform simulation forms an important aspect of our work - if you can simulate it, you understand it